Finding Strong Gravitational Lenses with Residual Neural Networks

Measuring gravitational lensing by galaxies is the only way to directly study the elusive dark matter. However, gravitational lensing is a very rare phenomenon (~1 in 10,000 galaxies). Our goal is to find new strong gravitational lenses using deep neural networks (“neural nets”). We train our neural nets on a hand-labeled set of images, consisting of both lenses and non-lenses (“the training sample”). We then apply the trained neural nets to a “validation set” to assess the accuracy and precision of its predictions. Given the rarity of lenses, we cannot tolerate a false positive rate higher than 0.1%. This is to minimize or possibly eliminate human inspection. This is an extremely high bar for Machine Learning (“ML”) algorithms. Our data sets are selected from real observational data. Utilizing real data has not been attempted before. In this project we update and modify an existing neural net model, originally created by a team at Carnegie Mellon University (CMU) written in Theano, a python library used for ML. After training on real, observed data the neural network recommended ~40,000 recommendations from a sample of 15 million galaxies. All recommendations were inspected by hand, from which there were hundreds of high probability candidates for strong lensing

Retrospective Search for Strongly Lensed Supernovae in the DESI Legacy Imaging Surveys

The introduction of deep wide-field surveys in recent years and the adoption of machine learning techniques have led to the discoveries of $\mathcal{O}(10^4)$ strong gravitational lensing systems and candidates. However, the discovery of multiply lensed transients remains a rarity. Lensed transients and especially lensed supernovae are invaluable tools to cosmology as they allow us to constrain cosmological parameters via lens modeling and the measurements of their time delays. In this paper, we develop a pipeline to perform a targeted lensed transient search. We apply this pipeline to 5807 strong lenses and candidates, identified in the literature, in the DESI Legacy Imaging Surveys Data Release 9 (DR9) footprint. For each system, we analyze every exposure in all observed bands (DECam $g$, $r$, and $z$). Our pipeline finds, groups, and ranks detections that are in sufficient proximity temporally and spatially. After the first round of inspection, for promising candidate systems, we further examine the newly available DR10 data (with additional $i$ and $\textrm{Y}$ bands). Here we present our targeted lensed supernova search pipeline and seven new lensed supernova candidates, including a very likely lensed supernova $-$ probably a Type Ia $-$ in a system with an Einstein radius of $\sim 1.5''$.Comment: 53 pages, 50 figures, 3 table

Transcriptional response of Mexican axolotls to \u3ci\u3eAmbystoma tigrinum\u3c/i\u3e virus (ATV) infection

Background Very little is known about the immunological responses of amphibians to pathogens that are causing global population declines. We used a custom microarray gene chip to characterize gene expression responses of axolotls (Ambystoma mexicanum) to an emerging viral pathogen, Ambystoma tigrinum virus (ATV). Result At 0, 24, 72, and 144 hours post-infection, spleen and lung samples were removed for estimation of host mRNA abundance and viral load. A total of 158 up-regulated and 105 down-regulated genes were identified across all time points using statistical and fold level criteria. The presumptive functions of these genes suggest a robust innate immune and antiviral gene expression response is initiated by A. mexicanum as early as 24 hours after ATV infection. At 24 hours, we observed transcript abundance changes for genes that are associated with phagocytosis and cytokine signaling, complement, and other general immune and defense responses. By 144 hours, we observed gene expression changes indicating host-mediated cell death, inflammation, and cytotoxicity. Conclusion Although A. mexicanum appears to mount a robust innate immune response, we did not observe gene expression changes indicative of lymphocyte proliferation in the spleen, which is associated with clearance of Frog 3 iridovirus in adult Xenopus. We speculate that ATV may be especially lethal to A. mexicanum and related tiger salamanders because they lack proliferative lymphocyte responses that are needed to clear highly virulent iridoviruses. Genes identified from this study provide important new resources to investigate ATV disease pathology and host-pathogen dynamics in natural populations

DESI-253.2534+26.8843: A New Einstein Cross Spectroscopically Confirmed with VLT/MUSE and Modeled with GIGA-Lens

Gravitational lensing provides unique insights into astrophysics and cosmology, including the determination of galaxy mass profiles and constraining cosmological parameters. We present spectroscopic confirmation and lens modeling of the strong lensing system DESI-253.2534+26.8843, discovered in the Dark Energy Spectroscopic Instrument (DESI) Legacy Imaging Surveys data. This system consists of a massive elliptical galaxy surrounded by four blue images forming an Einstein Cross pattern. We obtained spectroscopic observations of this system using the Multi Unit Spectroscopic Explorer (MUSE) on ESO's Very Large Telescope (VLT) and confirmed its lensing nature. The main lens, which is the elliptical galaxy, has a redshift of $z_{L1} = 0.636\pm 0.001$, while the spectra of the background source images are typical of a starburst galaxy and have a redshift of $z_s = 2.597 \pm 0.001$. Additionally, we identified a faint galaxy foreground of one of the lensed images, with a redshift of $z_{L2} = 0.386$. We employed the GIGA-Lens modeling code to characterize this system and determined the Einstein radius of the main lens to be $\theta_{E} =2.520{''}_{-0.031}^{+0.032}$, which corresponds to a velocity dispersion of $\sigma$ = 379 $\pm$ 2 km s$^{-1}$. Our study contributes to a growing catalog of this rare kind of strong lensing systems and demonstrates the effectiveness of spectroscopic integral field unit observations and advanced modeling techniques in understanding the properties of these systems.Comment: Accepted for publication in ApJ

Discovering New Strong Gravitational Lenses in the DESI Legacy Imaging Surveys

We have conducted a search for new strong gravitational lensing systems in the Dark Energy Spectroscopic Instrument Legacy Imaging Surveys’ Data Release 8. We use deep residual neural networks, building on previous work presented in Huang et al. (2020). These surveys together cover approximately one third of the sky visible from the northern hemisphere, reaching a z-band AB magnitude of ∼ 22.5. We compile a training sample that consists of known lensing systems as well as non-lenses in the Legacy Surveys and the Dark Energy Survey. After applying our trained neural networks to the survey data, we visually inspect and rank images with probabilities above a threshold. Here we present 1210 new strong lens candidates

Retrospective Search for Strongly Lensed Supernovae in the DESI Legacy Imaging Surveys

The introduction of deep wide-field surveys in recent years and the adoption of machine-learning techniques have led to the discoveries of O (104) strong gravitational lensing systems and candidates. However, the discovery of multiply-lensed transients remains a rarity. Lensed transients and especially lensed supernovae are invaluable tools to cosmology because they allow us to constrain cosmological parameters via lens modeling and the measurements of their time delays. In this paper, we develop a pipeline to perform a targeted lensed transient search. We apply this pipeline to 5807 strong lenses and candidates, which were identified in the literature, in the DESI Legacy Imaging Surveys Data Release 9 (DR9) footprint. For each system, we analyze every exposure in all of the observed bands (DECam g, r, and z). Our pipeline finds, groups, and ranks detections that are in sufficient proximity temporally and spatially. After the first round of inspection, for promising candidate systems, we further examine the newly available DR10 data (with additional i and Y bands). Here we present our targeted lensed supernova search pipeline and seven new lensed supernova candidates, including a very likely lensed supernova—probably a Type Ia—in a system with an Einstein radius of ∼1.″5

Transcriptional response of Mexican axolotls to Ambystoma tigrinum virus (ATV) infection

BACKGROUND: Very little is known about the immunological responses of amphibians to pathogens that are causing global population declines. We used a custom microarray gene chip to characterize gene expression responses of axolotls (Ambystoma mexicanum) to an emerging viral pathogen, Ambystoma tigrinum virus (ATV). RESULT: At 0, 24, 72, and 144 hours post-infection, spleen and lung samples were removed for estimation of host mRNA abundance and viral load. A total of 158 up-regulated and 105 down-regulated genes were identified across all time points using statistical and fold level criteria. The presumptive functions of these genes suggest a robust innate immune and antiviral gene expression response is initiated by A. mexicanum as early as 24 hours after ATV infection. At 24 hours, we observed transcript abundance changes for genes that are associated with phagocytosis and cytokine signaling, complement, and other general immune and defense responses. By 144 hours, we observed gene expression changes indicating host-mediated cell death, inflammation, and cytotoxicity. CONCLUSION: Although A. mexicanum appears to mount a robust innate immune response, we did not observe gene expression changes indicative of lymphocyte proliferation in the spleen, which is associated with clearance of Frog 3 iridovirus in adult Xenopus. We speculate that ATV may be especially lethal to A. mexicanum and related tiger salamanders because they lack proliferative lymphocyte responses that are needed to clear highly virulent iridoviruses. Genes identified from this study provide important new resources to investigate ATV disease pathology and host-pathogen dynamics in natural populations

Genotypes_microsatellites_six_regions

The genotype data (eight microsatellite loci) for all individuals from each of two regions of Rana pretiosa and four regions of Rana luteiventris are provided. There is a csv file for each region. Within each region, the data are organized by sampling site (see Table 1 for locality information)

Data from: Regional variation in drivers of connectivity for two frog species (Rana pretiosa and R. luteiventris) from the U.S. Pacific Northwest

Comparative landscape genetics has uncovered high levels of variation in which landscape factors affect connectivity among species and regions. However, the relative importance of species traits vs. environmental variation for predicting landscape patterns of connectivity is unresolved. We provide evidence from a landscape genetics study of two sister taxa of frogs, the Oregon spotted frog (Rana pretiosa) and the Columbia spotted frog (R. luteiventris) in Oregon and Idaho, USA. Rana pretiosa is relatively more dependent on moisture for dispersal than R. luteiventris for dispersal, so if species traits influence connectivity, we predicted that connectivity among R. pretiosa populations would be more positively associated with moisture than R. luteiventris. However, if environmental differences are important drivers of gene flow, we predicted that connectivity would be more positively related to moisture in arid regions. We tested these predictions using eight microsatellite loci and gravity models in two R. pretiosa regions and four R. luteiventris regions (n = 1,168 frogs). In R. pretiosa, but not R. luteiventris, connectivity was positively related to mean annual precipitation, supporting our first prediction. In contrast, connectivity was not more positively related to moisture in more arid regions. Various temperature metrics were important predictors for both species and in all regions, but the directionality of their effects varied. Our results indicate that connectivity in R. pretiosa may be negatively impacted by reduction in mean annual precipitation. Overall, the pattern of variation in drivers of connectivity was consistent with predictions based on species traits rather than on environmental variation

Transcriptomics of Tasmanian Devil (Sarcophilus Harrisii) Ear Tissue Reveals Homogeneous Gene Expression Patterns across a Heterogeneous Landscape

In an era of unprecedented global change, exploring patterns of gene expression among wild populations across their geographic range is crucial for characterizing adaptive potential. RNA-sequencing studies have successfully characterized gene expression differences among populations experiencing divergent environmental conditions in a wide variety of taxa. However, few of these studies have identified transcriptomic signatures to multivariate, environmental stimuli among populations in their natural environments. Herein, we aim to identify environmental and sex-driven patterns of gene expression in the Tasmanian devil (Sarcophilus harrisii), a critically endangered species that occupies a heterogeneous environment. We performed RNA-sequencing on ear tissue biopsies from adult male and female devils from three populations at the extremes of their geographic range. There were no transcriptome-wide patterns of differential gene expression that would be suggestive of significant, environmentally-driven transcriptomic responses. The general lack of transcriptome-wide variation in gene expression levels across the devil's geographic range is consistent with previous studies that documented low levels of genetic variation in the species. However, genes previously implicated in local adaptation to abiotic environment in devils were enriched for differentially expressed genes. Additionally, three modules of co-expressed genes were significantly associated with either population of origin or sex